Private company revenue is never publicly disclosed in the UK unless the company elects to file full accounts or exceeds the large company threshold. For the portion of the UK private mid-market that files abbreviated accounts, which is the majority of the deal-relevant universe in the five-to-fifty million pound range, no revenue figure appears in the public record at all.
This does not mean that revenue is unobservable. It means that revenue must be triangulated from proxy variables that are available in the public record or through near-public sources. The accuracy of any single proxy is modest. The combination of multiple proxies, each capturing a different dimension of the business's activity, produces an estimate that is good enough for sizing and prioritisation purposes, if not for investment committee use.
What follows is a description of the four sources we have found most useful and their respective contributions to a triangulated estimate. Each has structural strengths and structural weaknesses. The combination reduces the noise considerably.
Source One: Balance Sheet Debtors
Trade debtors (the amounts owed to the company by customers at the balance sheet date) appear in abbreviated accounts because they are a balance sheet item rather than an income statement item. This is one of the more reliable revenue proxies for B2B businesses with relatively stable payment terms.
The mechanics are straightforward. If a business has year-end trade debtors of one million pounds and its customers pay on average sixty-day terms, the implied annualised revenue is approximately six million pounds. The formula is: revenue estimate = (trade debtors / average debtor days) x 365.
The challenge is that debtor days are not disclosed and must be estimated from sector norms. For UK industrials, typical B2B payment terms range from thirty to seventy days, with considerable variation by sub-segment and customer type. Government and large corporate customers typically pay more slowly than small business customers. A company with a public sector contract mix will have different debtor days than a company selling to owner-managed businesses.
We build sector-specific debtor day ranges from the subset of companies in each sector that do file full accounts, and apply those ranges to the abbreviated-account universe. The result is a revenue band (lower bound at slow debtor days, upper bound at fast debtor days) rather than a point estimate. For most purposes, that band is precise enough to distinguish a five million pound company from a twenty million pound company.
Source Two: Net Fixed Assets
Fixed assets at net book value give a capital intensity signal. For businesses with significant physical plant, net fixed assets are a reasonable size proxy through the lens of revenue-to-asset ratios common in the sub-segment.
Revenue-to-asset ratios vary considerably by business type. A specialist printing company with significant press equipment might generate two to three pounds of revenue per pound of net fixed assets. A precision engineering business with high-value CNC machinery might generate four to six pounds. A service business with minimal plant might generate ten to twenty pounds of revenue per pound of assets. These are sector-specific multipliers that we calibrate from the companies that do file full accounts.
Fixed assets are particularly useful for industrial businesses, where the physical scale of the operation has a fairly direct relationship to revenue capacity. They are less useful for professional services businesses or asset-light distributors. We weight this source more heavily for industrials and less heavily for services-oriented companies in our triangulation.
One complication is the impact of lease accounting under FRS 102. Since the UK adoption of right-of-use asset accounting for larger companies, leased premises and vehicles appear as fixed assets in a way they did not previously. For companies that switched from FRS for Smaller Entities to FRS 102, the balance sheet comparability across time periods requires adjustment. We flag this in our methodology for companies where the fixed asset figure appears to have stepped up significantly in a period that aligns with the accounting standard transition.
Source Three: ONS Payroll and Employment Data
The Office for National Statistics publishes detailed payroll and employment data at sector and regional level, including average earnings by SOC (Standard Occupational Classification) code. This data, combined with an estimate of the company's headcount and workforce composition, gives a wage cost estimate that can be converted into a revenue estimate through sector-specific labour cost margins.
The headcount source for UK private companies is principally the confirmation statement employee count (for larger companies) and, for many mid-market companies, the note in the directors' report disclosing average employee numbers. Hiring data from job postings, normalised against sector norms, fills gaps where the filed headcount is outdated or unavailable.
The conversion from wage cost to revenue requires a labour cost margin assumption. For an industrial services business where labour is the primary cost input, wage costs might represent forty to fifty-five percent of revenue. For a distribution business where cost of goods sold dominates, labour cost as a percentage of revenue is much lower. We build these ratios from sector-level accounts data at industry level, cross-referenced against the ONS Gross Value Added surveys by sector.
This source is the noisiest of the four because it compounds multiple estimates: headcount (estimated), average wage (based on ONS sectoral norms, not company-specific data), and labour cost margin (based on sector averages). However, it provides a genuinely independent triangulation point that does not rely on balance sheet items, which makes it useful for checking consistency with the balance sheet-derived estimates.
Source Four: Tender and Contract Award Data
For companies that work on public sector contracts, the government's contract award data (published on Contracts Finder and, for higher-value contracts, Find a Tender Service) provides a direct revenue signal where it exists. A company appearing regularly in contract awards of a particular size has a visible revenue floor in its public sector work. This does not capture private sector revenue, but for businesses with meaningful public sector exposure, it anchors the estimate.
Contract data is particularly useful for companies in sectors with high public sector concentration: care and social work, facilities management on public estate, waste management, certain specialist construction activities, and healthcare services. For these sub-segments, contract awards can be the most precise source available, because they are actual disclosed transaction values rather than estimates.
The limitation is coverage. Many UK private companies have minimal public sector revenue, in which case contract data provides no signal. And for companies with a mix of public and private revenue, the contract data gives a floor but does not bound the upside. We treat this as a conditional source: high weight when relevant, zero weight when it is not applicable to the company's business model.
Combining the Sources: What the Triangulation Looks Like
In practice, we combine these four sources through a weighted average that reflects their individual reliability for the specific company and sub-sector. A source that produces an outlier estimate relative to the others receives less weight in the final triangulation, with the divergence flagged as a data quality note.
The output is a revenue band expressed as a lower and upper estimate, typically covering a range of thirty to fifty percent around the central estimate. For prioritisation purposes, this is sufficient to distinguish size tiers. A company estimated at ten to fifteen million pounds of revenue is in a materially different category from one estimated at forty to sixty million pounds, regardless of the uncertainty within each band.
We are explicit in our deliverables about the methodology and its limitations. The revenue estimate is a sizing proxy for target prioritisation, not a figure that should be used in financial modelling or valuation work. Any deal team that wants a reliable revenue figure for a company in our maps will need to obtain it through direct engagement. What the triangulation does is tell you which companies are worth that engagement.